# How to get a GLM where formula is programmatically generated

**URL:** <https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519>\
**Category:** New to Julia\
**Tags:** dataframes, glm\
**Created:** [July 22, 2020, 9:41pm UTC](https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519 "2020-07-22T21:41:24Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![mkarikom](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mkarikom/32/7096_2.png) [@mkarikom](https://discourse.julialang.org/u/mkarikom)\
**Post date:** [July 22, 2020, 9:41pm UTC](https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519/1 "2020-07-22T21:41:24Z")

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I have a DataFrame and need to build a model where the predictors follow some naming scheme.

For the example `data` below, suppose the scheme is “!=y”:

```julia
using DataFrames
using GLM

data = DataFrame(y=[22.1,20.1,7.1,9.1,1000,200],
                 x1=[1.1,2.1,3.1,4.1,10,100.2],
                 x2=[1,2,3,4.0,11.2,100.1])

```

Can anyone suggest a modification to Ex.2 below that would make the models in Ex.1 (`ols1`) and Ex.2 (`ols2`) equivalent?

Please note that while `ols2` does not run, I’m looking for something of comparable terseness, if possible.

**Ex 1:**

```julia
ols1 = GLM.lm(@formula(y ~ x1 + x2), data)
y ~ 1 + x1 + x2

Coefficients:
────────────────────────────────────────────────────────────────────────────
              Estimate Std. Error t value Pr(>|t|) Lower 95% Upper 95%
────────────────────────────────────────────────────────────────────────────
(Intercept) 84.4784 4.76541 17.7274 0.0004 69.3127 99.644
x1 -745.249 8.33275 -89.4361 <1e-5 -771.767 -718.73
x2 747.144 8.34614 89.5196 <1e-5 720.582 773.705

```

**Ex.2**

```julia
preds = Symbol.(names(data)[findall(names(data) .!= "y")])
2-element Array{String,1}:
 "x1"
 "x2"

ols2 = GLM.lm(@formula(y ~ preds), data)
ERROR: type NamedTuple has no field preds

```

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<div class="post-metadata">

**Author:** ![CameronBieganek](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/cameronbieganek/32/6915_2.png) [@CameronBieganek](https://discourse.julialang.org/u/CameronBieganek)\
**Post date:** [July 22, 2020, 11:36pm UTC](https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519/2 "2020-07-22T23:36:53Z")

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You can probably make use of `Terms` objects, as described [here](https://juliastats.org/StatsModels.jl/stable/formula/#Constructing-a-formula-programmatically-1).

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**Author:** ![dave.f.kleinschmidt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/dave.f.kleinschmidt/32/55_2.png) [@dave.f.kleinschmidt](https://discourse.julialang.org/u/dave.f.kleinschmidt)\
**Post date:** [August 16, 2020, 4:08pm UTC](https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519/3 "2020-08-16T16:08:57Z")

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Cameron is exactly right. These two forms are exactly equivalent:

```julia
julia> using StatsModels

julia> (Term(:y) ~ Term(:x1) + Term(:x2)) == @formula(y ~ x1 + x2)
true

```

As @nilshg pointed out in [this post](https://discourse.julialang.org/t/using-all-independent-variables-with-formula-in-a-multiple-linear-model/43691/5), this is actually the expression that’s generated by the formula macro:

```julia
julia> @macroexpand @formula(y ~ x1 + x2)
:(StatsModels.Term(:y) ~ StatsModels.Term(:x1) + StatsModels.Term(:x2))

```

---

<div class="post-metadata">

**Author:** ![dave.f.kleinschmidt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/dave.f.kleinschmidt/32/55_2.png) [@dave.f.kleinschmidt](https://discourse.julialang.org/u/dave.f.kleinschmidt)\
**Post date:** [September 1, 2020, 3:56pm UTC](https://discourse.julialang.org/t/how-to-get-a-glm-where-formula-is-programmatically-generated/43519/4 "2020-09-01T15:56:39Z")

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@nilshg just added support for creating a `Term` from a string (available in [v0.6.14, which should automerge soon](https://github.com/JuliaRegistries/General/pull/20638)), so you can now do something like

```julia
terms = term.(names(data))
f = terms[1] ~ sum(terms[2:end]) # assuming first column is "y"
ols2 = lm(f, data)

```